Immu-Mela

Immu-Mela enables exploration and integrative analysis of multi-omics immuno-genomic data to identify genomic signatures associated with immune checkpoint blockade (ICB) response in melanoma.

Key Features:

• ICB association analysis: Assesses associations between immune checkpoint blockade (ICB) treatment responses and multi-omics features in melanoma, including genetic, transcriptomic, immune cell profiles, and single-cell populations.
• Integrative pairwise analysis: Performs integrative analysis of any two genomic features to examine interactions across data types.
• User dataset co-analysis: Supports uploading and co-analysis of external datasets (not restricted to melanoma or any specific cancer type) with consolidated cohorts to identify and validate genomic signatures relevant to ICB responses.
• Consolidated immuno-genomic datasets: Aggregates large-scale immuno-genomic datasets relevant to melanoma ICB studies that were previously difficult to access.
• Feature discovery: Has identified both known and novel genomic features associated with ICB response in melanoma cohorts.

Scientific Applications:

• Predictive biomarker discovery: Identifies genomic signatures predictive of ICB treatment response in melanoma patients.
• Biomarker validation: Facilitates validation of candidate genomic biomarkers by co-analyzing user-supplied datasets with existing cohorts, including non-melanoma data.
• Mechanistic hypothesis generation: Enables investigation of relationships among genetic, transcriptomic, and immune cell features to generate hypotheses about mechanisms underlying ICB response.

Methodology:

Performs pairwise integrative analyses and association testing between multi-omics features (genetic, transcriptomic, immune cell profiles, single-cell populations) and ICB responsiveness, and supports co-analysis of user-uploaded datasets with consolidated cohorts.